Putting things together

I’m not 100% happy with this one but when am I ever? Let’s get it out there.

And that’s kinda why I got off track. And it was an awesome detour. And we’ll get back to it. And I’m going to stop with the gimmick now.

But first,Combined WP48 take 5,6, eleventy? Let’s get on with it.

Just lie back and picture your favorite MVP candidate.

Because we also only stop for kittens (and the odd inspiration)

Ok, explanations first, fun and profit(?) second.If you’re new, welcome to my funhouse, feel free to peruse the Basics for background on the metrics used and remember that the numbers are made possible through the kind donations of Nerdnumbers .

What were doing here is looking at opponent adjusted Wins Produced. The goal is to get as close as possible to adding an individual opponent adjustment to the Wins Produced model. The driver for this has been the fact that currently Wins Produced divides defense up at the team level for all stats that are not in the boxscore and I have been trying for a while to get at this. Why? I don’t know call it a pet peeve.

The goal then is WP48 at the player level adjust for what the player does and what his opponent does.In layman’s terms instead of being compared to the average team, we compare you to the player on the other side. Sounds good but it’s a little difficult to achieve with publicly available data sources.

But that has never stopped me before.

What did I actually do? I worked out:

Classic WP48 for each player.

Opponent WP48 for each player by game based on time by position (this is Wins Produced by team based on deviation of the opponent from average) .

Used opponent WP48 to generate losses Produced by opponent.

Added them up into a number I’m calling Combined WP48 (by the simple expedient of taking the average)

Here’s the result:

More than a few fun conclusions come up. Top twenty in opponent Losses produced per 48:

Rank

Player

Current Team

1

Rajon Rondo

BOS

2

Dwight Howard

ORL

3

Kobe Bryant

LAL

4

James Jones

MIA

5

Kevin Durant

OKC

6

Gary Neal

SAS

7

Jodie Meeks

PHI

8

Richard Jefferson

SAS

9

Andre Iguodala

PHI

10

George Hill

SAS

11

Ron Artest

LAL

12

Ronnie Brewer

CHI

13

Marquis Daniels

14

Shannon Brown

LAL

15

Kyle Korver

CHI

16

Kevin Martin

HOU

17

Manu Ginobili

SAS

18

LeBron James

MIA

19

Andre Miller

POR

20

Andrew Bynum

LAL

Rondo is numbers #1 (which is very probably more than slightly helped by the Celts killer D). Howard is no surprise at number 2 (and Durant at 5 isn’t either , he keeps showing up when I do these things) . Kobe and James Jones are a surprise.

As for the MVP? I guess, I get to agree with Hollinger and call out the Big Man in Orlando.

Think you have to switch Ron and Kobe. Ron often covers the SG. He defends the better wing.

I still think you need to look at WP48 opp vs that opponent’s avg WP48.

I agree on Dwight. He’s the MVP.

To the Bargnani comment, he’s actually not a terrible man on man defender. He’s bad, but not terrible. He’s a horrific help defender, though. And bigs need good help defense. That’s why it seems like his teammates are outperforming him, but they’re not. Ben Wallace, on the other hand, has superb help D. But also he’s old now and Detroit sucks. Good defenders will appear to suck on poor defensive teams since they’re wasted.

Unfortunately, it’s very hard to incorporate help defense, which is probably the majority of a big man’s defense in today’s NBA, into the stats. I’m not sure how Arturo could tackle that without using differentials of some kind.

Then you do this. Say for Love his counterpart is .100. And say the team is .200. What you do is assign help d like this: Take the difference of the average opp team and subtract is by the counterpart and divide based on position.

Say, C = .3, PF = .3, SF = .15, SG = .15 and PG = .1

Then add it to the total.

So for Love, it would be .100 for counterpart plus+.03 for help defense (.3 x .1), so .130 is his Defensive WP48 measure.

I don’t know what values to put for each position. And maybe you only take the average WP of the other 4 players, not all 5, to determine opponent average WP48.

This is a cool idea. I wonder if loses produced would remain relatively constant (like WP) for a player that changed teams. And I’d guess that quantifying help defense would lead to +/- adjusted type problems.

I’d like to review this data further but find it somewhat hard with a picture this wide and don’t know any way to convert to excel directly. Any chance, as a general option, you could offer excel file links as well? Or for a wide picture like this, perhaps put the player name on the right and maybe in the middle too to aid reading across and knowing more easily which player’s line you are on?

SD,

I think I follow your overall concept but I think you’d have to give the counterpart rating a % of the total and then help defense the other part to get th scores of all to sum properly. Also having a fixed set of shares for distributing help defense credit and blame (as a simplifying assumption) is an option that Evan and I discussed on his site. Maybe it helps get closer on average but individuals with vary from their position average responsibility based on team scheme and how an offense attacks it and that ideally would be something to try to specify from the data instead of assuming. Perhaps the Synergy data on player involvement in plays with switches and joint shot defense could give the data for a pretty good statistical estimate. Perhaps this is what Arturo hinted at paying for.

Frequency of plays where a player didn’t help could be inferred and the impact of those failures to be involved could be estimated using certain simplifying assumptions.

I don’t think Synergy offers an evaluation of the defensive effort, at least in the public version. Some teams do that themselves for each shot defense. Both efforts and outcomes are worth knowing. Is not always 1 to 1. Would need clear standards. Was the close-out a good one or just going thru the motions?

Long story, short – Jones has played most of his minutes paired w/ LeBron, Bosh or Wade. He’s also played the majority of his minutes at SF. Playing the same position as LeBron & Wade MAY make you look good defensively thru the boxscore lens but it also reduces your marginal productivity because no one else at the position can be more productive than them (see http://miami-heat-index.blogspot.com/2011/01/heat-check-benching-john-hollinger.html).